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The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling by Margy Ross, Ralph Kimball

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Chapter 1. Dimensional Modeling Primer

In this first chapter we lay the groundwork for the case studies that follow. We'll begin by stepping back to consider data warehousing from a macro perspective. Some readers may be disappointed to learn that it is not all about tools and techniques—first and foremost, the data warehouse must consider the needs of the business. We'll drive stakes in the ground regarding the goals of the data warehouse while observing the uncanny similarities between the responsibilities of a data warehouse manager and those of a publisher. With this big-picture perspective, we'll explore the major components of the warehouse environment, including the role of normalized models. Finally, we'll close by establishing fundamental vocabulary for dimensional modeling. By the end of this chapter we hope that you'll have an appreciation for the need to be half DBA (database administrator) and half MBA (business analyst) as you tackle your data warehouse.

Note

Chapter 1 discusses the following concepts:

  • Business-driven goals of a data warehouse

  • Data warehouse publishing

  • Major components of the overall data warehouse

  • Importance of dimensional modeling for the data warehouse presentation area

  • Fact and dimension table terminology

  • Myths surrounding dimensional modeling

  • Common data warehousing pitfalls to avoid

Different Information Worlds

One of the most important assets of any organization is its information. This asset is almost always kept by an organization in two forms: the operational ...

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